Managing Spare Parts Inventory by Incorporating Holding Costs and Storage Constraints

A key factor for motivating intending buyers of raw materials is vendor responsiveness. Therefore, to meet demand, a pre-approved level of stocks is often maintained. In contrast, the decision to keep an uncontrolled amount of stock could be counter-productive with cost components associatedwith holding often ignored unintentionally. In this study, the objective is to develop a spare parts inventory model that incorporates ignored holding costs with a storage constraint for a motorcycle assembly plant (MAP). The inventory policy, structure of holding costs, and spare parts sales reports were consulted for relevant data. The spare parts were categorized and selected using ABC analysis. A spare parts inventory model, which considers ignored holding cost, was formulated. The model was executed using Lingo optimisation software release 18.0.56 to determine the pair of the orderquantity (ES) and reorder point. 177 spare part items were identified using ABC analysis. The partscategorisation revealed that 21, 31, 125 part items belong to categories A, B, and C with 81, 15 and 4% of annual sales value, respectively. From category A, nine items contributed significantly tooverall sales. The demand pattern for these items was probabilistic based on their coefficient of variation. The pair (ES) for items N, Z, AY, K, AM, J, P, AL and AZ are (174,688), (71,147), (78,150), (86,163), (18,15), (88,170), (128,118), (33,43) and (87,152), respectively. These pairs yielded atotal inventory cost of 2,177,363 when compared to the current total inventory investment of 6,800,000 resulting in a 67.9% cost reduction. A model to manage spare parts inventory with relevant holding cost components was developed for MAP to ensure the availability of items, maximize usage of storage space, and minimize total inventory cost.